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[ATen][CPU][Sparse] Use Third-Party Eigen for sparse add and addmm (#155357)

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This pull request adds the following ops for sparse matrices using Eigen library:
```python
    add(a_csr, b_csr)
    add(a_csc, b_csc)

    addmm(c_csr, a_csr, b_csr)
    addmm(c_csr, a_csr, b_csc)
    addmm(c_csr, a_csc, b_csc)
    addmm(c_csr, a_csc, b_csr)

    addmm(c_csc, a_csr, b_csr)
    addmm(c_csc, a_csr, b_csc)
    addmm(c_csc, a_csc, b_csc)
    addmm(c_csc, a_csc, b_csr)
```

Currently, the operations for sparse matrices on CPU are available through MKL only. The non-existence of MKL on `aarch64` causes the unavailability of these ops on any machines with ARM based CPUs, including Apple Silicon, AWS Graviton and NVIDIA Grace. This PR addresses this issue by using Eigen as a backend for the above ops.

This is a re-factored version of my previous PR #101814. The main difference with the old one, this does not enable Eigen by default.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/155357
Approved by: https://github.com/pearu, https://github.com/eqy
This commit is contained in:
Aidyn-A
2025-08-20 15:44:54 +00:00
committed by PyTorch MergeBot
parent 90ea9ccefe
commit ce048de608
13 changed files with 423 additions and 8 deletions
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CMakeLists.txt
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@ -289,6 +289,7 @@ option(USE_PRECOMPILED_HEADERS "Use pre-compiled headers to accelerate build."
option(USE_PROF "Use profiling" OFF)
option(USE_PYTORCH_QNNPACK "Use ATen/QNNPACK (quantized 8-bit operators)" ON)
option(USE_SNPE "Use Qualcomm's SNPE library" OFF)
option(USE_EIGEN_SPARSE "Use Eigen Sparse Matrices" OFF)
option(USE_SYSTEM_EIGEN_INSTALL
"Use system Eigen instead of the one under third_party" OFF)
cmake_dependent_option(